Vipin Arora

Bio: Vipin Arora is an academic researcher from Energy Information Administration. The author has contributed to research in topics: Interest rate & Natural gas. The author has an hindex of 11, co-authored 31 publications receiving 407 citations. Previous affiliations of Vipin Arora include Australian National University.

Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence

Abstract: Do oil prices and stock markets move in tandem or in opposite directions? The complex and time varying relationship between oil prices and stock markets has caught the attention of the financial press, investors, policymakers, researchers, and the general public in recent years. In light of such attention, this paper reviews research on the oil price and stock market relationship. The majority of papers we survey study the impacts of oil markets on stock markets, whereas, little research in the reverse direction exists. Our review finds that the causal effects between oil and stock markets depend heavily on whether research is performed using aggregate stock market indices, sectorial indices, or firm-level data and whether stock markets operate in net oil-importing or net oil-exporting countries. Additionally, conclusions vary depending on whether studies use symmetric or asymmetric changes in the price of oil, or whether they focus on unexpected changes in oil prices. Finally, we find that most studies show oil price volatility transmits to stock market volatility, and that including measures of stock market performance improves forecasts of oil prices and oil price volatility. Several important avenues for further research are identified.

An Application of Models of Speculative Behaviour to Oil Prices

Abstract: We estimate three different models of speculative behaviour using oil price data. There are two major results: (i) The three-regime model of Brooks and Katsaris (2005) and a three-regime variant of van Norden and Schaller (2002) fit the oil price data reasonably well; and (ii) Both models show that the probabilities of being in a bubble collapsing state and a bubble expansion state spike in late-2008/early-2009. This provides some support for the claim by Phillips and Yu (2010) and Gilbert (2010) that a bubble in oil prices existed for short period in 2008.

Estimates of the Price Elasticities of Natural Gas Supply and Demand in the United States

Abstract: I estimate short and long-run price elasticities of U.S. natural gas supply and demand. For robustness, the estimates are based on data of varying frequencies and samples, some of which include the recent U.S. shale gas boom. Aside from the numbers themselves, there are two main conclusions. As expected, U.S. price elasticities of natural gas supply are higher in both the short and long-run when the e�ffects of shale are included in the sample (post-2007). The calculated price elasticities of natural gas demand are also more responsive than recent estimates, but in-line with earlier ones.

Forecasting, Structural Time Series Models and the Kalman Filter

Abstract: In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Transaction cost economics

Abstract: In the debate on no-regret potentials, transaction costs are a rather controversial issue On the one hand, the controversy concerns the level of transaction costs related to energy saving measures Existing cost-benefit analyses for energy saving measures are often criticised for being incomplete because, allegedly, they would not fully account for transaction costs Depending on the level of transaction costs, this negligence is more or less severe Some studies, e g Sutherland (1991), hold that transaction costs are so high that they challenge favourable results of quantitative cost-benefit analyses and explain why energy-efficient technologies are not adopted Other studies implicitly assume transactions costs to be zero (e g Lovins, Lovins 1991; Landwehr et al 1996) As pointed out, e g by Golove and Eto (1996, p 24) this aspect of the debate suggests a need to empirically quantify transaction costs and integrate them in the cost-benefit assessment of the measures considered